JP2017536209A5

JP2017536209A5 -

Info

Publication number: JP2017536209A5
Application number: JP2017529823A
Authority: JP
Filing date: 2015-11-30
Publication date: 2019-03-22
Anticipated expiration: 2035-11-30

Claims

A magnetic resonance imaging system for collecting magnetic resonance data from a subject in an imaging zone, the magnetic resonance imaging system comprising:
A memory for storing machine-executable instructions and pulse sequence data, the pulse sequence data including commands for collecting magnetic resonance data using n-point Dickson magnetic resonance imaging , N is an integer greater than or equal to 2, memory;
A processor for controlling the magnetic resonance imaging system, and the execution of the instructions is executed by the processor,
Controlling the magnetic resonance imaging system with the pulse sequence data to collect magnetic resonance data;
Constructing two phase candidate maps using the magnetic resonance data according to the n-point Dixon magnetic resonance imaging method, each of the two phase candidate maps being in an image space, of the two phase candidate maps Each contains a set of voxels, each voxel having a phase map value; and
Identifying the set of object voxels in the set of voxels using an object identification algorithm;
Identifying a set of boundary voxels and internal voxels within the set of object voxels using a boundary identification algorithm;
Generating a selection phase candidate map having the set of voxels in the memory;
Selecting a selected phase map value for at least part of the set of boundary voxels in the selected phase map from the two phase candidate maps, wherein the phase map value is a value of the two phase candidate maps; Comparing the phase candidate map values for each voxel of the set of boundary voxels at each and selecting the candidate phase map value that exhibits the lowest fat to water ratio;
Calculating a phase map value of the object voxel according to a phase candidate selection algorithm, the inputs for the candidate selection algorithm being the two phase candidate maps and the set of boundary voxels in the selected phase map And including the sorted phase map values for the at least a portion of
Magnetic resonance imaging system.

The object identification algorithm identifies a voxel of the set of voxels as an object voxel because the voxel has an absolute value greater than x times the standard deviation of noise in the two phase candidate maps, and n input data 2. The magnetic resonance imaging of claim 1, wherein the magnetic resonance imaging has an amplitude at least y times the maximum amplitude in the set, x is a first predetermined value, and y is a second predetermined value that is 1 or less. system.

x is between 3 and 5, between 3.5 and 4.5, between 2 and 4 and between 4 and 6, and y is between 0.06 and 0.08, between 0.05 and 0.07, and between 0.07 and 0.09 3. The magnetic resonance imaging system according to claim 2, wherein the magnetic resonance imaging system is any of the following: between 1/14 and 1/16, between 1/13 and 1/15, and between 1/15 and 1/17.

Said set of voxels has an edge, the boundary identification algorithm in the processor, thereby identifying the boundary voxels from the object voxels are connected by the route to the edge via said set of background voxels claim 1 serial mounting a magnetic resonance imaging system.

The boundary identification algorithm identifies the boundary voxel by identifying to the processor an object voxel selected from the set of object voxels adjacent to at least one background voxel selected from the set of background voxels. to identify the set, according to claim 1 Symbol mounting a magnetic resonance imaging system.

The phase candidate selection algorithm causes the processor to calculate the phase map value of the object voxel:
Interpolating the phase map value of the object voxel using the phase map value initially selected for each voxel of the set of boundary voxels;
-Executing according to a sequential iterative algorithm by correcting the phase map value of the object voxel with the two candidate phase maps;
Claim 1 Symbol mounting a magnetic resonance imaging system.

The sequential iterative algorithm is:
Selecting a provisional phase map value for each voxel of the set of internal voxels by selecting a phase map value from the two phase candidate maps closest to the phase map value in the selected phase candidate map;
Replace the phase map value for each object voxel with the provisional phase map value;
Smoothing the phase map value of the object voxel using a spatial smoothing filter;
Repeating the iterative algorithm until the phase map value for each voxel of the set of object voxels converges to a predetermined criterion;
The magnetic resonance imaging system according to claim 6.

The magnetic resonance imaging system of claim 7, wherein the phase map value of the object voxel is interpolated using the spatial smoothing filter.

The sequential iterative algorithm is:
Selecting a phase map value for the local voxel by selecting a phase map value from the two phase candidate maps that is closest to the value of the local voxel in the selected phase candidate map, the local voxel being Performing a step selected from the set of internal voxels and within a predetermined distance from the set of boundary voxels;
Moving the local voxels from the set of internal voxels to the set of boundary voxels;
Interpolating the values of internal voxels within the set of object voxels using a sorted phase map value for each voxel of the set of boundary voxels;
Repeating the iterative algorithm until the entire set of inner voxels is an element of the set of boundary voxels;
The magnetic resonance imaging system according to claim 6.

The memory further includes a prior phase map, wherein the phase candidate selection algorithm causes the processor to calculate a phase map value of an object voxel by solving a minimization algorithm, and the minimization algorithm includes the boundary A first penalty term that measures a deviation of a voxel phase map value from a corresponding voxel in the prior phase map, and the minimization algorithm measures a spatial variation in the phase map value of the object voxel The magnetic resonance imaging system of claim 6, having a second penalty term.

The phase candidate selection algorithm, the processor to calculate the phase map values of the interior voxels according TRWS algorithm, according to claim 6 Symbol mounting a magnetic resonance imaging system.

The machine-executable instructions further cause the processor, the magnetic resonance data and the sorting is reconstructed magnetic resonance image using the phase map, claim 1 Symbol mounting a magnetic resonance imaging system.

A computer program having machine-executable instructions for execution by a processor that controls a magnetic resonance imaging system to collect magnetic resonance data from a subject in an imaging zone, the magnetic resonance imaging system comprising: A memory for storing sequence data, wherein the pulse sequence data includes commands for collecting magnetic resonance data using n-point Dickson magnetic resonance imaging, wherein n is 2 or more; Execution of the instructions is to the processor:
Controlling the magnetic resonance imaging system with the pulse sequence data to collect magnetic resonance data;
Constructing two phase candidate maps using the magnetic resonance data according to the n-point Dixon magnetic resonance imaging method, each of the two phase candidate maps being in an image space, of the two phase candidate maps Each contains a set of voxels, each voxel having a phase map value; and
Identifying a set of object voxels in the set of voxels using an object identification algorithm;
Identifying a set of boundary voxels and internal voxels within the set of object voxels using a boundary identification algorithm;
Generating a selection phase candidate map in the memory, wherein the selection phase candidate map includes the set of voxels;
Selecting a selected phase map value for at least a portion of the set of boundary voxels in the selected phase map from the two phase candidate maps, wherein the phase map value is a value of the two phase candidate maps; Selected by selecting a candidate phase map value indicating the lowest fat-to-water ratio by comparing the candidate phase map values for each voxel of the set of boundary voxels at each;
Calculating a phase map value of the object voxel according to a phase candidate selection algorithm, wherein the input for the phase candidate selection algorithm is the two phase candidate maps and the boundary voxels of the selected phase map Including the screening phase map values for the at least part of the set,
Computer program.

A method of operating a magnetic resonance imaging system to collect magnetic resonance data from a subject in an imaging zone, the method comprising:
Controlling the magnetic resonance imaging system with pulse sequence data to collect magnetic resonance data, wherein the pulse sequence data is collected using n-point Dickson magnetic resonance imaging Including a command to do, n is 2 or more, and a stage;
Constructing two phase candidate maps using the magnetic resonance data according to the n-point Dixon magnetic resonance imaging method, each of the two phase candidate maps being in an image space, of the two phase candidate maps Each contains a set of voxels, each voxel having a phase map value; and
Identifying a set of object voxels in the set of voxels using an object identification algorithm;
Identifying a set of boundary voxels and a set of internal voxels within the set of object voxels using a boundary identification algorithm;
Generating a selection phase candidate map including the set of voxels;
Selecting a selected phase map value for at least a portion of the set of boundary voxels in the selected phase map from the two phase candidate maps, wherein the phase map value is a value of the two phase candidate maps; Selected by comparing the candidate phase map values for each voxel of the set of boundary voxels at each and selecting the candidate phase map value indicating the lowest fat to water ratio;
Calculating a phase map value of the object voxel according to a phase candidate selection algorithm, wherein the input for the phase candidate selection algorithm is the two phase candidate maps and the boundary voxels of the selected phase map Including the sorted phase map values for the at least part of the set.
Method.